Gold Portfolio Risk and Returns (Coronavirus)

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import math

import warnings
warnings.filterwarnings("ignore")

# fix_yahoo_finance is used to fetch data 
import yfinance as yf
yf.pdr_override()

# input
# Gold Stocks
symbols = ['AEM','AG','AGI','AU','AUG','AUY','AXU','BTG','CDE','CMCL','DRD','EGO','EXK','FNV','FSM','GFI','GOLD','GORO','GSS','GSV','HMY','IAG','KGC','KL','MAG','MUX','NEM','NG','OR','PAAS','PLG','PVG','RGLD','SA','SAND','SILV','SVM','TMQ','USAU','WPM']
start = '2019-12-01'
end = '2020-05-13'

df = pd.DataFrame()
for s in symbols:
    df[s] = yf.download(s,start,end)['Adj Close']

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from datetime import datetime
from dateutil import relativedelta

d1 = datetime.strptime(start, "%Y-%m-%d")
d2 = datetime.strptime(end, "%Y-%m-%d")
delta = relativedelta.relativedelta(d2,d1)
print('How many years of investing?')
print('%s years' % delta.years)

How many years of investing?
0 years

number_of_years = delta.years

days = (df.index[-1] - df.index[0]).days
days

162

df.head()

	AEM	AG	AGI	AU	AUG	AUY	AXU	BTG	CDE	CMCL	...	PLG	PVG	RGLD	SA	SAND	SILV	SVM	TMQ	USAU	WPM
Date
2019-12-02	59.825211	10.91	5.628248	18.809914	1.310	3.644445	1.78	3.711770	6.60	7.852439	...	1.34	10.01	116.652649	12.68	6.72	5.72	5.08	1.77	8.4	27.750179
2019-12-03	61.448833	11.26	5.707799	19.843315	1.430	3.723888	1.96	3.711770	7.22	8.236687	...	1.35	10.32	117.587624	13.37	6.92	6.11	5.25	1.79	8.2	28.158710
2019-12-04	61.130085	11.03	5.648136	19.674393	1.450	3.733819	2.10	3.721748	7.29	8.177571	...	1.38	10.39	116.602921	13.20	6.80	6.11	5.25	1.81	8.3	27.939499
2019-12-05	61.179890	11.23	5.658097	19.714140	1.430	3.743749	2.02	3.721748	7.24	8.246539	...	1.39	10.35	117.329018	13.29	6.88	6.17	5.36	1.92	8.3	27.959427
2019-12-06	60.084190	10.47	5.369215	18.650928	1.424	3.535211	1.92	3.621969	6.79	8.098752	...	1.36	10.13	113.042068	12.69	6.66	6.04	5.13	1.96	8.2	27.172258

5 rows × 40 columns

df.tail()

	AEM	AG	AGI	AU	AUG	AUY	AXU	BTG	CDE	CMCL	...	PLG	PVG	RGLD	SA	SAND	SILV	SVM	TMQ	USAU	WPM
Date
2020-05-06	63.330002	7.94	8.23	25.549999	1.04	4.87	1.68	5.42	3.84	12.604763	...	1.36	8.30	126.620003	14.22	8.21	7.11	3.83	1.60	5.04	42.020000
2020-05-07	65.540001	8.37	8.53	26.260000	1.08	5.07	1.79	5.67	4.06	13.409957	...	1.39	8.64	135.970001	14.64	8.56	7.90	4.04	1.65	5.11	43.730000
2020-05-08	65.889999	8.28	8.27	26.170000	1.12	5.24	1.77	5.49	4.17	13.737998	...	1.43	8.54	136.429993	14.50	7.99	7.65	4.17	1.76	5.10	43.380001
2020-05-11	64.550003	7.80	7.93	25.190001	1.14	5.07	1.75	5.21	4.21	13.668414	...	1.40	8.26	132.839996	13.81	7.72	7.15	4.00	1.79	5.01	42.630001
2020-05-12	64.230003	7.91	7.84	25.290001	1.12	5.08	1.71	5.16	4.00	13.141559	...	1.41	8.36	128.809998	14.48	7.85	7.00	3.90	1.79	4.85	42.340000

5 rows × 40 columns

plt.figure(figsize=(12,8))
plt.plot(df)
plt.title('Gold Stocks Closing Price')
plt.legend(labels=df.columns)

<matplotlib.legend.Legend at 0x137ff40a160>

# Normalize the data
normalize = (df - df.min())/ (df.max() - df.min())

plt.figure(figsize=(18,12))
plt.plot(normalize)
plt.title('Gold Stocks Normalize')
plt.legend(labels=normalize.columns)

<matplotlib.legend.Legend at 0x137ff49bcf8>

stock_rets = df.pct_change().dropna()

plt.figure(figsize=(12,8))
plt.plot(stock_rets)
plt.title('Gold Stocks Returns')
plt.legend(labels=stock_rets.columns)

<matplotlib.legend.Legend at 0x137ff57e4a8>

plt.figure(figsize=(12,8))
plt.plot(stock_rets.cumsum())
plt.title('Gold Stocks Returns Cumulative Sum')
plt.legend(labels=stock_rets.columns)

<matplotlib.legend.Legend at 0x137ff63be48>

sns.set(style='ticks')
ax = sns.pairplot(stock_rets, diag_kind='hist')

nplot = len(stock_rets.columns)
for i in range(nplot) :
    for j in range(nplot) :
        ax.axes[i, j].locator_params(axis='x', nbins=6, tight=True)

ax = sns.PairGrid(stock_rets)
ax.map_upper(plt.scatter, color='purple')
ax.map_lower(sns.kdeplot, color='blue')
ax.map_diag(plt.hist, bins=30)
for i in range(nplot) :
    for j in range(nplot) :
        ax.axes[i, j].locator_params(axis='x', nbins=6, tight=True)

plt.figure(figsize=(10,10))
corr = stock_rets.corr()

# plot the heatmap
sns.heatmap(corr, 
        xticklabels=corr.columns,
        yticklabels=corr.columns,
            cmap="Reds")

<matplotlib.axes._subplots.AxesSubplot at 0x137ae370ac8>

# Box plot
stock_rets.plot(kind='box',figsize=(24,8))

<matplotlib.axes._subplots.AxesSubplot at 0x137ba589f28>

rets = stock_rets.dropna()

plt.figure(figsize=(16,8))
plt.scatter(rets.std(), rets.mean(),alpha = 0.5)

plt.title('Stocks Risk & Returns')
plt.xlabel('Risk')
plt.ylabel('Expected Returns')
plt.grid(which='major')

for label, x, y in zip(rets.columns, rets.std(), rets.mean()):
    plt.annotate(
        label, 
        xy = (x, y), xytext = (50, 50),
        textcoords = 'offset points', ha = 'right', va = 'bottom',
        arrowprops = dict(arrowstyle = '-', connectionstyle = 'arc3,rad=-0.3'))

rets = stock_rets.dropna()
area = np.pi*20.0

sns.set(style='darkgrid')
plt.figure(figsize=(16,8))
plt.scatter(rets.std(), rets.mean(), s=area)
plt.xlabel("Risk", fontsize=15)
plt.ylabel("Expected Return", fontsize=15)
plt.title("Return vs. Risk for Stocks", fontsize=20)

for label, x, y in zip(rets.columns, rets.std(), rets.mean()) : 
    plt.annotate(label, xy=(x,y), xytext=(50, 0), textcoords='offset points',
                arrowprops=dict(arrowstyle='-', connectionstyle='bar,angle=180,fraction=-0.2'),
                bbox=dict(boxstyle="round", fc="w"))

rest_rets = rets.corr()
pair_value = rest_rets.abs().unstack()
pair_value.sort_values(ascending = False)

WPM   WPM     1.000000
OR    OR      1.000000
IAG   IAG     1.000000
KGC   KGC     1.000000
KL    KL      1.000000
MAG   MAG     1.000000
MUX   MUX     1.000000
NEM   NEM     1.000000
NG    NG      1.000000
PAAS  PAAS    1.000000
GSV   GSV     1.000000
PLG   PLG     1.000000
PVG   PVG     1.000000
RGLD  RGLD    1.000000
SA    SA      1.000000
SAND  SAND    1.000000
SILV  SILV    1.000000
SVM   SVM     1.000000
HMY   HMY     1.000000
GSS   GSS     1.000000
USAU  USAU    1.000000
CDE   CDE     1.000000
AG    AG      1.000000
AGI   AGI     1.000000
AU    AU      1.000000
AUG   AUG     1.000000
AUY   AUY     1.000000
AXU   AXU     1.000000
BTG   BTG     1.000000
CMCL  CMCL    1.000000
                ...   
TMQ   BTG     0.087340
BTG   TMQ     0.087340
TMQ   GFI     0.085255
GFI   TMQ     0.085255
HMY   TMQ     0.079441
TMQ   HMY     0.079441
      PVG     0.073869
PVG   TMQ     0.073869
EGO   TMQ     0.072637
TMQ   EGO     0.072637
      FNV     0.066144
FNV   TMQ     0.066144
TMQ   AEM     0.059039
AEM   TMQ     0.059039
TMQ   AUY     0.044645
AUY   TMQ     0.044645
TMQ   KGC     0.044411
KGC   TMQ     0.044411
TMQ   SAND    0.040304
SAND  TMQ     0.040304
OR    TMQ     0.023909
TMQ   OR      0.023909
      WPM     0.022105
WPM   TMQ     0.022105
AXU   TMQ     0.011575
TMQ   AXU     0.011575
      AGI     0.011411
AGI   TMQ     0.011411
TMQ   IAG     0.008734
IAG   TMQ     0.008734
Length: 1600, dtype: float64

# Normalized Returns Data
Normalized_Value = ((rets[:] - rets[:].min()) /(rets[:].max() - rets[:].min()))
Normalized_Value.head()

	AEM	AG	AGI	AU	AUG	AUY	AXU	BTG	CDE	CMCL	...	PLG	PVG	RGLD	SA	SAND	SILV	SVM	TMQ	USAU	WPM
Date
2019-12-03	0.571671	0.501030	0.428014	0.595441	0.945628	0.526956	0.669396	0.538385	0.526586	0.550020	...	0.359858	0.594880	0.490616	0.497709	0.511746	0.667176	0.444942	0.560527	0.167907	0.557826
2019-12-04	0.470938	0.349518	0.377195	0.450609	0.624919	0.470616	0.613100	0.546088	0.368366	0.404893	...	0.386737	0.535438	0.454441	0.352829	0.389839	0.475610	0.389981	0.560148	0.191822	0.438932
2019-12-05	0.489641	0.460781	0.402445	0.474651	0.510137	0.470595	0.405463	0.538385	0.337276	0.445270	...	0.359464	0.509305	0.486670	0.394985	0.465168	0.503201	0.424392	0.708843	0.183722	0.483825
2019-12-06	0.431295	0.213176	0.293272	0.346940	0.549793	0.298726	0.383833	0.461552	0.233424	0.377105	...	0.306963	0.466526	0.392278	0.282836	0.351960	0.416412	0.319507	0.589108	0.175719	0.331330
2019-12-09	0.434410	0.391923	0.371957	0.466392	0.613556	0.454491	0.428315	0.546280	0.375051	0.382552	...	0.346268	0.540603	0.475838	0.344556	0.430834	0.480262	0.428399	0.511357	0.199923	0.447125

5 rows × 40 columns

Normalized_Value.corr()

	AEM	AG	AGI	AU	AUG	AUY	AXU	BTG	CDE	CMCL	...	PLG	PVG	RGLD	SA	SAND	SILV	SVM	TMQ	USAU	WPM
AEM	1.000000	0.716171	0.704508	0.691787	0.447281	0.726255	0.475904	0.731054	0.546997	0.440000	...	0.333989	0.528840	0.818947	0.661417	0.640156	0.509744	0.630430	0.059039	0.512706	0.598790
AG	0.716171	1.000000	0.791753	0.801603	0.504139	0.860556	0.686384	0.835238	0.724907	0.578958	...	0.410342	0.675012	0.821534	0.812760	0.846470	0.710684	0.776763	0.131902	0.543361	0.787543
AGI	0.704508	0.791753	1.000000	0.792343	0.452560	0.884097	0.574448	0.876508	0.620540	0.422315	...	0.321479	0.751575	0.772881	0.816042	0.887098	0.498064	0.772822	0.011411	0.445851	0.685765
AU	0.691787	0.801603	0.792343	1.000000	0.388629	0.830383	0.571879	0.844513	0.572036	0.497586	...	0.376693	0.661482	0.835494	0.776467	0.827329	0.571948	0.665614	0.112267	0.510963	0.705699
AUG	0.447281	0.504139	0.452560	0.388629	1.000000	0.509729	0.492305	0.571070	0.543673	0.529912	...	0.427806	0.480939	0.377901	0.557340	0.478749	0.471873	0.573457	0.146242	0.389957	0.426671
AUY	0.726255	0.860556	0.884097	0.830383	0.509729	1.000000	0.642051	0.890247	0.646369	0.549600	...	0.368266	0.746835	0.798605	0.837649	0.860116	0.619532	0.776503	0.044645	0.504232	0.816021
AXU	0.475904	0.686384	0.574448	0.571879	0.492305	0.642051	1.000000	0.622609	0.609493	0.425654	...	0.412043	0.523543	0.491858	0.673928	0.667365	0.699218	0.566359	-0.011575	0.242945	0.623129
BTG	0.731054	0.835238	0.876508	0.844513	0.571070	0.890247	0.622609	1.000000	0.644435	0.573449	...	0.426625	0.756939	0.795214	0.806970	0.867387	0.663162	0.755940	0.087340	0.455042	0.728408
CDE	0.546997	0.724907	0.620540	0.572036	0.543673	0.646369	0.609493	0.644435	1.000000	0.437185	...	0.299316	0.520679	0.615682	0.685951	0.617200	0.429700	0.697452	0.181290	0.396586	0.532811
CMCL	0.440000	0.578958	0.422315	0.497586	0.529912	0.549600	0.425654	0.573449	0.437185	1.000000	...	0.407544	0.421160	0.486044	0.473051	0.496487	0.461988	0.418980	0.141618	0.438943	0.490253
DRD	0.638247	0.731286	0.720647	0.793615	0.440601	0.763533	0.595384	0.764820	0.569113	0.506124	...	0.269331	0.570324	0.728897	0.672031	0.750502	0.556965	0.616802	-0.089271	0.388258	0.612824
EGO	0.608498	0.733566	0.686020	0.755511	0.462450	0.764409	0.579738	0.775172	0.473145	0.582517	...	0.426050	0.654860	0.655311	0.689894	0.730827	0.583489	0.619751	0.072637	0.408054	0.658395
EXK	0.589933	0.814630	0.740022	0.675852	0.586405	0.770802	0.646857	0.765607	0.718645	0.558906	...	0.393309	0.655595	0.599376	0.794217	0.786803	0.575660	0.775760	0.153267	0.417469	0.641858
FNV	0.714940	0.784162	0.820509	0.781988	0.454944	0.850646	0.548243	0.810536	0.576521	0.463739	...	0.373915	0.648895	0.717492	0.764883	0.813606	0.566581	0.704589	0.066144	0.524603	0.786445
FSM	0.703578	0.856621	0.724424	0.747326	0.533512	0.755080	0.675403	0.765160	0.598825	0.480492	...	0.452696	0.595344	0.734417	0.734560	0.766619	0.721989	0.692118	0.108947	0.506511	0.672481
GFI	0.669311	0.773480	0.806406	0.923740	0.412518	0.813501	0.577955	0.856051	0.551097	0.465341	...	0.396647	0.690593	0.776950	0.738575	0.821797	0.553456	0.680976	0.085255	0.440393	0.660996
GOLD	0.739557	0.822749	0.765809	0.810258	0.534085	0.870390	0.618280	0.827573	0.639052	0.581797	...	0.360620	0.604278	0.834743	0.788321	0.768845	0.640240	0.707939	0.093226	0.523623	0.790815
GORO	0.692809	0.782797	0.726417	0.745831	0.549462	0.807721	0.638217	0.791244	0.647857	0.553462	...	0.447396	0.688288	0.720796	0.775176	0.774372	0.590985	0.719667	0.168669	0.391388	0.640997
GSS	0.513602	0.633769	0.652766	0.520419	0.552001	0.664171	0.500986	0.661731	0.537670	0.445325	...	0.282134	0.539183	0.526046	0.581482	0.585813	0.441697	0.731631	0.250560	0.426606	0.526879
GSV	0.555216	0.612928	0.572814	0.553812	0.522862	0.615774	0.299868	0.631739	0.511994	0.605746	...	0.395719	0.441058	0.608464	0.528275	0.571258	0.435291	0.702251	0.249432	0.594284	0.501335
HMY	0.567740	0.683020	0.664781	0.824810	0.491876	0.720455	0.537887	0.773852	0.459611	0.529564	...	0.453382	0.569697	0.649294	0.664920	0.722817	0.530010	0.631430	0.079441	0.356501	0.632560
IAG	0.627314	0.727570	0.812365	0.738071	0.502259	0.825327	0.618069	0.832390	0.537507	0.487103	...	0.248060	0.676378	0.674594	0.763422	0.848869	0.502691	0.701179	0.008734	0.327813	0.643590
KGC	0.761611	0.837400	0.911490	0.850501	0.496708	0.943865	0.645598	0.885454	0.632974	0.506704	...	0.370641	0.721410	0.817601	0.823069	0.887149	0.588997	0.769065	0.044411	0.487644	0.779922
KL	0.701141	0.802880	0.789092	0.841998	0.488583	0.788042	0.586059	0.865551	0.621176	0.463356	...	0.362746	0.653294	0.825413	0.735324	0.817787	0.603962	0.736522	0.132892	0.481284	0.616822
MAG	0.571962	0.800495	0.732601	0.694199	0.451312	0.750378	0.731369	0.735069	0.639467	0.415006	...	0.331627	0.614129	0.655977	0.786680	0.799076	0.671585	0.713208	0.127837	0.449636	0.635647
MUX	0.632705	0.779181	0.658420	0.755333	0.420381	0.776790	0.512351	0.695784	0.575624	0.476715	...	0.397822	0.594653	0.700130	0.741835	0.675618	0.569908	0.573989	0.207841	0.513034	0.727427
NEM	0.775696	0.818786	0.773433	0.773589	0.511523	0.846247	0.602632	0.816490	0.668866	0.549845	...	0.365454	0.638657	0.815754	0.806181	0.721503	0.604616	0.708405	0.095422	0.556756	0.809567
NG	0.664483	0.786550	0.855963	0.755268	0.416079	0.861551	0.596541	0.775437	0.676808	0.387630	...	0.306546	0.695109	0.721870	0.843842	0.840868	0.462009	0.717681	0.101921	0.470282	0.713559
OR	0.598227	0.773634	0.869827	0.733543	0.493297	0.834563	0.681400	0.812745	0.674880	0.396004	...	0.344794	0.743209	0.671201	0.872597	0.874250	0.550910	0.736698	0.023909	0.400490	0.739686
PAAS	0.793424	0.878781	0.815309	0.835650	0.516562	0.896010	0.538443	0.869370	0.692184	0.592470	...	0.394784	0.646848	0.871735	0.785521	0.792567	0.611917	0.802032	0.154941	0.580242	0.757556
PLG	0.333989	0.410342	0.321479	0.376693	0.427806	0.368266	0.412043	0.426625	0.299316	0.407544	...	1.000000	0.297361	0.319991	0.423920	0.352560	0.455028	0.372465	0.287884	0.379402	0.383889
PVG	0.528840	0.675012	0.751575	0.661482	0.480939	0.746835	0.523543	0.756939	0.520679	0.421160	...	0.297361	1.000000	0.564952	0.717200	0.732364	0.470111	0.651618	0.073869	0.364181	0.645217
RGLD	0.818947	0.821534	0.772881	0.835494	0.377901	0.798605	0.491858	0.795214	0.615682	0.486044	...	0.319991	0.564952	1.000000	0.723545	0.748147	0.570344	0.689535	0.153031	0.585401	0.665803
SA	0.661417	0.812760	0.816042	0.776467	0.557340	0.837649	0.673928	0.806970	0.685951	0.473051	...	0.423920	0.717200	0.723545	1.000000	0.827057	0.588066	0.728943	0.131347	0.557659	0.754304
SAND	0.640156	0.846470	0.887098	0.827329	0.478749	0.860116	0.667365	0.867387	0.617200	0.496487	...	0.352560	0.732364	0.748147	0.827057	1.000000	0.605068	0.730795	0.040304	0.377682	0.729300
SILV	0.509744	0.710684	0.498064	0.571948	0.471873	0.619532	0.699218	0.663162	0.429700	0.461988	...	0.455028	0.470111	0.570344	0.588066	0.605068	1.000000	0.503344	0.113847	0.415889	0.650873
SVM	0.630430	0.776763	0.772822	0.665614	0.573457	0.776503	0.566359	0.755940	0.697452	0.418980	...	0.372465	0.651618	0.689535	0.728943	0.730795	0.503344	1.000000	0.134738	0.485607	0.648744
TMQ	0.059039	0.131902	0.011411	0.112267	0.146242	0.044645	-0.011575	0.087340	0.181290	0.141618	...	0.287884	0.073869	0.153031	0.131347	0.040304	0.113847	0.134738	1.000000	0.237951	0.022105
USAU	0.512706	0.543361	0.445851	0.510963	0.389957	0.504232	0.242945	0.455042	0.396586	0.438943	...	0.379402	0.364181	0.585401	0.557659	0.377682	0.415889	0.485607	0.237951	1.000000	0.456016
WPM	0.598790	0.787543	0.685765	0.705699	0.426671	0.816021	0.623129	0.728408	0.532811	0.490253	...	0.383889	0.645217	0.665803	0.754304	0.729300	0.650873	0.648744	0.022105	0.456016	1.000000

40 rows × 40 columns

normalized_rets = Normalized_Value.corr()
normalized_pair_value = normalized_rets.abs().unstack()
normalized_pair_value.sort_values(ascending = False)

WPM   WPM     1.000000
OR    OR      1.000000
IAG   IAG     1.000000
KGC   KGC     1.000000
KL    KL      1.000000
MAG   MAG     1.000000
MUX   MUX     1.000000
NEM   NEM     1.000000
NG    NG      1.000000
PAAS  PAAS    1.000000
GSV   GSV     1.000000
PLG   PLG     1.000000
PVG   PVG     1.000000
RGLD  RGLD    1.000000
SA    SA      1.000000
SAND  SAND    1.000000
SILV  SILV    1.000000
SVM   SVM     1.000000
HMY   HMY     1.000000
GSS   GSS     1.000000
USAU  USAU    1.000000
CDE   CDE     1.000000
AG    AG      1.000000
AGI   AGI     1.000000
AU    AU      1.000000
AUG   AUG     1.000000
AUY   AUY     1.000000
AXU   AXU     1.000000
BTG   BTG     1.000000
CMCL  CMCL    1.000000
                ...   
TMQ   BTG     0.087340
BTG   TMQ     0.087340
TMQ   GFI     0.085255
GFI   TMQ     0.085255
HMY   TMQ     0.079441
TMQ   HMY     0.079441
      PVG     0.073869
PVG   TMQ     0.073869
EGO   TMQ     0.072637
TMQ   EGO     0.072637
      FNV     0.066144
FNV   TMQ     0.066144
TMQ   AEM     0.059039
AEM   TMQ     0.059039
TMQ   AUY     0.044645
AUY   TMQ     0.044645
TMQ   KGC     0.044411
KGC   TMQ     0.044411
TMQ   SAND    0.040304
SAND  TMQ     0.040304
OR    TMQ     0.023909
TMQ   OR      0.023909
      WPM     0.022105
WPM   TMQ     0.022105
AXU   TMQ     0.011575
TMQ   AXU     0.011575
      AGI     0.011411
AGI   TMQ     0.011411
TMQ   IAG     0.008734
IAG   TMQ     0.008734
Length: 1600, dtype: float64

print("Stock returns: ")
print(rets.mean())
print('-' * 50)
print("Stock risks:")
print(rets.std())

Stock returns: 
AEM     0.001426
AG     -0.001522
AGI     0.004778
AU      0.004299
AUG    -0.000550
AUY     0.004270
AXU     0.001783
BTG     0.004370
CDE    -0.001518
CMCL    0.005892
DRD     0.009417
EGO     0.002910
EXK    -0.002053
FNV     0.003750
FSM     0.001687
GFI     0.006066
GOLD    0.004556
GORO    0.000167
GSS    -0.001672
GSV     0.002743
HMY     0.004012
IAG     0.001567
KGC     0.005539
KL      0.000665
MAG     0.002446
MUX    -0.000310
NEM     0.004958
NG      0.005584
OR      0.001986
PAAS    0.002181
PLG     0.003272
PVG    -0.000308
RGLD    0.001991
SA      0.002890
SAND    0.002849
SILV    0.003237
SVM     0.000373
TMQ     0.001344
USAU    0.001165
WPM     0.004355
dtype: float64
--------------------------------------------------
Stock risks:
AEM     0.039499
AG      0.052698
AGI     0.060617
AU      0.057724
AUG     0.041567
AUY     0.050570
AXU     0.065967
BTG     0.052778
CDE     0.078391
CMCL    0.050785
DRD     0.064093
EGO     0.061169
EXK     0.056984
FNV     0.032165
FSM     0.059565
GFI     0.067190
GOLD    0.035489
GORO    0.057420
GSS     0.043186
GSV     0.078153
HMY     0.064018
IAG     0.054417
KGC     0.052840
KL      0.047669
MAG     0.064114
MUX     0.055404
NEM     0.034608
NG      0.054173
OR      0.049132
PAAS    0.054527
PLG     0.076743
PVG     0.051226
RGLD    0.047112
SA      0.059063
SAND    0.054221
SILV    0.053523
SVM     0.076470
TMQ     0.050266
USAU    0.134714
WPM     0.033102
dtype: float64

table = pd.DataFrame()
table['Returns'] = rets.mean()
table['Risk'] = rets.std()
table.sort_values(by='Returns')

	Returns	Risk
EXK	-0.002053	0.056984
GSS	-0.001672	0.043186
AG	-0.001522	0.052698
CDE	-0.001518	0.078391
AUG	-0.000550	0.041567
MUX	-0.000310	0.055404
PVG	-0.000308	0.051226
GORO	0.000167	0.057420
SVM	0.000373	0.076470
KL	0.000665	0.047669
USAU	0.001165	0.134714
TMQ	0.001344	0.050266
AEM	0.001426	0.039499
IAG	0.001567	0.054417
FSM	0.001687	0.059565
AXU	0.001783	0.065967
OR	0.001986	0.049132
RGLD	0.001991	0.047112
PAAS	0.002181	0.054527
MAG	0.002446	0.064114
GSV	0.002743	0.078153
SAND	0.002849	0.054221
SA	0.002890	0.059063
EGO	0.002910	0.061169
SILV	0.003237	0.053523
PLG	0.003272	0.076743
FNV	0.003750	0.032165
HMY	0.004012	0.064018
AUY	0.004270	0.050570
AU	0.004299	0.057724
WPM	0.004355	0.033102
BTG	0.004370	0.052778
GOLD	0.004556	0.035489
AGI	0.004778	0.060617
NEM	0.004958	0.034608
KGC	0.005539	0.052840
NG	0.005584	0.054173
CMCL	0.005892	0.050785
GFI	0.006066	0.067190
DRD	0.009417	0.064093

table.sort_values(by='Risk')

	Returns	Risk
FNV	0.003750	0.032165
WPM	0.004355	0.033102
NEM	0.004958	0.034608
GOLD	0.004556	0.035489
AEM	0.001426	0.039499
AUG	-0.000550	0.041567
GSS	-0.001672	0.043186
RGLD	0.001991	0.047112
KL	0.000665	0.047669
OR	0.001986	0.049132
TMQ	0.001344	0.050266
AUY	0.004270	0.050570
CMCL	0.005892	0.050785
PVG	-0.000308	0.051226
AG	-0.001522	0.052698
BTG	0.004370	0.052778
KGC	0.005539	0.052840
SILV	0.003237	0.053523
NG	0.005584	0.054173
SAND	0.002849	0.054221
IAG	0.001567	0.054417
PAAS	0.002181	0.054527
MUX	-0.000310	0.055404
EXK	-0.002053	0.056984
GORO	0.000167	0.057420
AU	0.004299	0.057724
SA	0.002890	0.059063
FSM	0.001687	0.059565
AGI	0.004778	0.060617
EGO	0.002910	0.061169
HMY	0.004012	0.064018
DRD	0.009417	0.064093
MAG	0.002446	0.064114
AXU	0.001783	0.065967
GFI	0.006066	0.067190
SVM	0.000373	0.076470
PLG	0.003272	0.076743
GSV	0.002743	0.078153
CDE	-0.001518	0.078391
USAU	0.001165	0.134714

rf = 0.01
table['Sharpe Ratio'] = (table['Returns'] - rf) / table['Risk']
table

	Returns	Risk	Sharpe Ratio
AEM	0.001426	0.039499	-0.217057
AG	-0.001522	0.052698	-0.218639
AGI	0.004778	0.060617	-0.086149
AU	0.004299	0.057724	-0.098757
AUG	-0.000550	0.041567	-0.253818
AUY	0.004270	0.050570	-0.113307
AXU	0.001783	0.065967	-0.124570
BTG	0.004370	0.052778	-0.106671
CDE	-0.001518	0.078391	-0.146934
CMCL	0.005892	0.050785	-0.080886
DRD	0.009417	0.064093	-0.009097
EGO	0.002910	0.061169	-0.115909
EXK	-0.002053	0.056984	-0.211511
FNV	0.003750	0.032165	-0.194307
FSM	0.001687	0.059565	-0.139564
GFI	0.006066	0.067190	-0.058546
GOLD	0.004556	0.035489	-0.153390
GORO	0.000167	0.057420	-0.171243
GSS	-0.001672	0.043186	-0.270279
GSV	0.002743	0.078153	-0.092857
HMY	0.004012	0.064018	-0.093535
IAG	0.001567	0.054417	-0.154973
KGC	0.005539	0.052840	-0.084430
KL	0.000665	0.047669	-0.195822
MAG	0.002446	0.064114	-0.117825
MUX	-0.000310	0.055404	-0.186097
NEM	0.004958	0.034608	-0.145691
NG	0.005584	0.054173	-0.081512
OR	0.001986	0.049132	-0.163122
PAAS	0.002181	0.054527	-0.143393
PLG	0.003272	0.076743	-0.087667
PVG	-0.000308	0.051226	-0.201224
RGLD	0.001991	0.047112	-0.170006
SA	0.002890	0.059063	-0.120377
SAND	0.002849	0.054221	-0.131878
SILV	0.003237	0.053523	-0.126360
SVM	0.000373	0.076470	-0.125894
TMQ	0.001344	0.050266	-0.172210
USAU	0.001165	0.134714	-0.065581
WPM	0.004355	0.033102	-0.170535

table['Max Returns'] = rets.max()

table['Min Returns'] = rets.min()

table['Median Returns'] = rets.median()

total_return = stock_rets[-1:].transpose()
table['Total Return'] = 100 * total_return
table

	Returns	Risk	Sharpe Ratio	Max Returns	Min Returns	Median Returns	Total Return
AEM	0.001426	0.039499	-0.217057	0.164597	-0.156319	0.000812	-0.495739
AG	-0.001522	0.052698	-0.218639	0.205000	-0.141553	-0.005413	1.410252
AGI	0.004778	0.060617	-0.086149	0.290870	-0.192946	0.001764	-1.134927
AU	0.004299	0.057724	-0.098757	0.232181	-0.205929	0.002628	0.396984
AUG	-0.000550	0.041567	-0.253818	0.104762	-0.137255	0.000000	-1.754384
AUY	0.004270	0.050570	-0.113307	0.182432	-0.157143	0.004762	0.197234
AXU	0.001783	0.065967	-0.124570	0.275510	-0.251969	-0.008130	-2.285712
BTG	0.004370	0.052778	-0.106671	0.161074	-0.187861	0.004785	-0.959697
CDE	-0.001518	0.078391	-0.146934	0.346008	-0.186441	0.001678	-4.988124
CMCL	0.005892	0.050785	-0.080886	0.222910	-0.163722	0.003802	-3.854547
DRD	0.009417	0.064093	-0.009097	0.234414	-0.201195	0.006622	-0.323632
EGO	0.002910	0.061169	-0.115909	0.320479	-0.193985	-0.001121	-0.112110
EXK	-0.002053	0.056984	-0.211511	0.271930	-0.195804	-0.005952	4.411760
FNV	0.003750	0.032165	-0.194307	0.110634	-0.095818	0.003599	-0.233696
FSM	0.001687	0.059565	-0.139564	0.219828	-0.225564	0.000000	1.863352
GFI	0.006066	0.067190	-0.058546	0.267813	-0.237589	0.004862	1.270647
GOLD	0.004556	0.035489	-0.153390	0.151802	-0.103331	0.002731	0.076866
GORO	0.000167	0.057420	-0.171243	0.146616	-0.180723	0.000000	-4.627251
GSS	-0.001672	0.043186	-0.270279	0.198157	-0.102459	0.000000	1.214574
GSV	0.002743	0.078153	-0.092857	0.378378	-0.270270	-0.011905	-7.042247
HMY	0.004012	0.064018	-0.093535	0.168067	-0.249097	0.003135	5.763690
IAG	0.001567	0.054417	-0.154973	0.211268	-0.190476	-0.003333	1.117317
KGC	0.005539	0.052840	-0.084430	0.190000	-0.153846	0.004132	0.434779
KL	0.000665	0.047669	-0.195822	0.148540	-0.175737	0.001385	-3.339018
MAG	0.002446	0.064114	-0.117825	0.286942	-0.212389	-0.000918	-1.143361
MUX	-0.000310	0.055404	-0.186097	0.219472	-0.123905	0.000000	-0.949367
NEM	0.004958	0.034608	-0.145691	0.140182	-0.111161	0.004134	-0.746626
NG	0.005584	0.054173	-0.081512	0.276968	-0.117021	0.002328	0.000000
OR	0.001986	0.049132	-0.163122	0.271357	-0.143855	0.002132	2.034257
PAAS	0.002181	0.054527	-0.143393	0.234649	-0.210000	0.004337	-0.788131
PLG	0.003272	0.076743	-0.087667	0.358974	-0.190141	0.000000	0.714285
PVG	-0.000308	0.051226	-0.201224	0.195804	-0.211076	-0.001940	1.210647
RGLD	0.001991	0.047112	-0.170006	0.238794	-0.214262	0.001320	-3.033724
SA	0.002890	0.059063	-0.120377	0.287157	-0.176201	0.003058	4.851550
SAND	0.002849	0.054221	-0.131878	0.218415	-0.167969	0.001475	1.683939
SILV	0.003237	0.053523	-0.126360	0.186640	-0.169279	0.000000	-2.097903
SVM	0.000373	0.076470	-0.125894	0.371429	-0.237452	-0.005415	-2.499998
TMQ	0.001344	0.050266	-0.172210	0.157895	-0.175676	-0.004386	0.000000
USAU	0.001165	0.134714	-0.065581	1.228916	-0.276596	-0.008081	-3.193619
WPM	0.004355	0.033102	-0.170535	0.098425	-0.090875	0.002732	-0.680274

table['Average Return Days'] = (1 + total_return)**(1 / days) - 1
table

	Returns	Risk	Sharpe Ratio	Max Returns	Min Returns	Median Returns	Total Return	Average Return Days
AEM	0.001426	0.039499	-0.217057	0.164597	-0.156319	0.000812	-0.495739	-0.000031
AG	-0.001522	0.052698	-0.218639	0.205000	-0.141553	-0.005413	1.410252	0.000086
AGI	0.004778	0.060617	-0.086149	0.290870	-0.192946	0.001764	-1.134927	-0.000070
AU	0.004299	0.057724	-0.098757	0.232181	-0.205929	0.002628	0.396984	0.000024
AUG	-0.000550	0.041567	-0.253818	0.104762	-0.137255	0.000000	-1.754384	-0.000109
AUY	0.004270	0.050570	-0.113307	0.182432	-0.157143	0.004762	0.197234	0.000012
AXU	0.001783	0.065967	-0.124570	0.275510	-0.251969	-0.008130	-2.285712	-0.000143
BTG	0.004370	0.052778	-0.106671	0.161074	-0.187861	0.004785	-0.959697	-0.000060
CDE	-0.001518	0.078391	-0.146934	0.346008	-0.186441	0.001678	-4.988124	-0.000316
CMCL	0.005892	0.050785	-0.080886	0.222910	-0.163722	0.003802	-3.854547	-0.000243
DRD	0.009417	0.064093	-0.009097	0.234414	-0.201195	0.006622	-0.323632	-0.000020
EGO	0.002910	0.061169	-0.115909	0.320479	-0.193985	-0.001121	-0.112110	-0.000007
EXK	-0.002053	0.056984	-0.211511	0.271930	-0.195804	-0.005952	4.411760	0.000267
FNV	0.003750	0.032165	-0.194307	0.110634	-0.095818	0.003599	-0.233696	-0.000014
FSM	0.001687	0.059565	-0.139564	0.219828	-0.225564	0.000000	1.863352	0.000114
GFI	0.006066	0.067190	-0.058546	0.267813	-0.237589	0.004862	1.270647	0.000078
GOLD	0.004556	0.035489	-0.153390	0.151802	-0.103331	0.002731	0.076866	0.000005
GORO	0.000167	0.057420	-0.171243	0.146616	-0.180723	0.000000	-4.627251	-0.000292
GSS	-0.001672	0.043186	-0.270279	0.198157	-0.102459	0.000000	1.214574	0.000075
GSV	0.002743	0.078153	-0.092857	0.378378	-0.270270	-0.011905	-7.042247	-0.000451
HMY	0.004012	0.064018	-0.093535	0.168067	-0.249097	0.003135	5.763690	0.000346
IAG	0.001567	0.054417	-0.154973	0.211268	-0.190476	-0.003333	1.117317	0.000069
KGC	0.005539	0.052840	-0.084430	0.190000	-0.153846	0.004132	0.434779	0.000027
KL	0.000665	0.047669	-0.195822	0.148540	-0.175737	0.001385	-3.339018	-0.000210
MAG	0.002446	0.064114	-0.117825	0.286942	-0.212389	-0.000918	-1.143361	-0.000071
MUX	-0.000310	0.055404	-0.186097	0.219472	-0.123905	0.000000	-0.949367	-0.000059
NEM	0.004958	0.034608	-0.145691	0.140182	-0.111161	0.004134	-0.746626	-0.000046
NG	0.005584	0.054173	-0.081512	0.276968	-0.117021	0.002328	0.000000	0.000000
OR	0.001986	0.049132	-0.163122	0.271357	-0.143855	0.002132	2.034257	0.000124
PAAS	0.002181	0.054527	-0.143393	0.234649	-0.210000	0.004337	-0.788131	-0.000049
PLG	0.003272	0.076743	-0.087667	0.358974	-0.190141	0.000000	0.714285	0.000044
PVG	-0.000308	0.051226	-0.201224	0.195804	-0.211076	-0.001940	1.210647	0.000074
RGLD	0.001991	0.047112	-0.170006	0.238794	-0.214262	0.001320	-3.033724	-0.000190
SA	0.002890	0.059063	-0.120377	0.287157	-0.176201	0.003058	4.851550	0.000292
SAND	0.002849	0.054221	-0.131878	0.218415	-0.167969	0.001475	1.683939	0.000103
SILV	0.003237	0.053523	-0.126360	0.186640	-0.169279	0.000000	-2.097903	-0.000131
SVM	0.000373	0.076470	-0.125894	0.371429	-0.237452	-0.005415	-2.499998	-0.000156
TMQ	0.001344	0.050266	-0.172210	0.157895	-0.175676	-0.004386	0.000000	0.000000
USAU	0.001165	0.134714	-0.065581	1.228916	-0.276596	-0.008081	-3.193619	-0.000200
WPM	0.004355	0.033102	-0.170535	0.098425	-0.090875	0.002732	-0.680274	-0.000042

initial_value = df.iloc[0]
ending_value = df.iloc[-1]
table['CAGR'] = ((ending_value / initial_value) ** (252.0 / days)) -1
table

	Returns	Risk	Sharpe Ratio	Max Returns	Min Returns	Median Returns	Total Return	Average Return Days	CAGR
AEM	0.001426	0.039499	-0.217057	0.164597	-0.156319	0.000812	-0.495739	-0.000031	0.116850
AG	-0.001522	0.052698	-0.218639	0.205000	-0.141553	-0.005413	1.410252	0.000086	-0.393586
AGI	0.004778	0.060617	-0.086149	0.290870	-0.192946	0.001764	-1.134927	-0.000070	0.674600
AU	0.004299	0.057724	-0.098757	0.232181	-0.205929	0.002628	0.396984	0.000024	0.584840
AUG	-0.000550	0.041567	-0.253818	0.104762	-0.137255	0.000000	-1.754384	-0.000109	-0.216319
AUY	0.004270	0.050570	-0.113307	0.182432	-0.157143	0.004762	0.197234	0.000012	0.676337
AXU	0.001783	0.065967	-0.124570	0.275510	-0.251969	-0.008130	-2.285712	-0.000143	-0.060501
BTG	0.004370	0.052778	-0.106671	0.161074	-0.187861	0.004785	-0.959697	-0.000060	0.669365
CDE	-0.001518	0.078391	-0.146934	0.346008	-0.186441	0.001678	-4.988124	-0.000316	-0.541128
CMCL	0.005892	0.050785	-0.080886	0.222910	-0.163722	0.003802	-3.854547	-0.000243	1.227861
DRD	0.009417	0.064093	-0.009097	0.234414	-0.201195	0.006622	-0.323632	-0.000020	2.574258
EGO	0.002910	0.061169	-0.115909	0.320479	-0.193985	-0.001121	-0.112110	-0.000007	0.210574
EXK	-0.002053	0.056984	-0.211511	0.271930	-0.195804	-0.005952	4.411760	0.000267	-0.467793
FNV	0.003750	0.032165	-0.194307	0.110634	-0.095818	0.003599	-0.233696	-0.000014	0.748085
FSM	0.001687	0.059565	-0.139564	0.219828	-0.225564	0.000000	1.863352	0.000114	-0.014063
GFI	0.006066	0.067190	-0.058546	0.267813	-0.237589	0.004862	1.270647	0.000078	0.930777
GOLD	0.004556	0.035489	-0.153390	0.151802	-0.103331	0.002731	0.076866	0.000005	0.971097
GORO	0.000167	0.057420	-0.171243	0.146616	-0.180723	0.000000	-4.627251	-0.000292	-0.230688
GSS	-0.001672	0.043186	-0.270279	0.198157	-0.102459	0.000000	1.214574	0.000075	-0.359784
GSV	0.002743	0.078153	-0.092857	0.378378	-0.270270	-0.011905	-7.042247	-0.000451	-0.023121
HMY	0.004012	0.064018	-0.093535	0.168067	-0.249097	0.003135	5.763690	0.000346	0.397169
IAG	0.001567	0.054417	-0.154973	0.211268	-0.190476	-0.003333	1.117317	0.000069	0.017434
KGC	0.005539	0.052840	-0.084430	0.190000	-0.153846	0.004132	0.434779	0.000027	1.048815
KL	0.000665	0.047669	-0.195822	0.148540	-0.175737	0.001385	-3.339018	-0.000210	-0.078083
MAG	0.002446	0.064114	-0.117825	0.286942	-0.212389	-0.000918	-1.143361	-0.000071	0.084323
MUX	-0.000310	0.055404	-0.186097	0.219472	-0.123905	0.000000	-0.949367	-0.000059	-0.270440
NEM	0.004958	0.034608	-0.145691	0.140182	-0.111161	0.004134	-0.746626	-0.000046	1.124296
NG	0.005584	0.054173	-0.081512	0.276968	-0.117021	0.002328	0.000000	0.000000	1.054380
OR	0.001986	0.049132	-0.163122	0.271357	-0.143855	0.002132	2.034257	0.000124	0.151788
PAAS	0.002181	0.054527	-0.143393	0.234649	-0.210000	0.004337	-0.788131	-0.000049	0.126419
PLG	0.003272	0.076743	-0.087667	0.358974	-0.190141	0.000000	0.714285	0.000044	0.082430
PVG	-0.000308	0.051226	-0.201224	0.195804	-0.211076	-0.001940	1.210647	0.000074	-0.244365
RGLD	0.001991	0.047112	-0.170006	0.238794	-0.214262	0.001320	-3.033724	-0.000190	0.166741
SA	0.002890	0.059063	-0.120377	0.287157	-0.176201	0.003058	4.851550	0.000292	0.229353
SAND	0.002849	0.054221	-0.131878	0.218415	-0.167969	0.001475	1.683939	0.000103	0.273505
SILV	0.003237	0.053523	-0.126360	0.186640	-0.169279	0.000000	-2.097903	-0.000131	0.369069
SVM	0.000373	0.076470	-0.125894	0.371429	-0.237452	-0.005415	-2.499998	-0.000156	-0.337137
TMQ	0.001344	0.050266	-0.172210	0.157895	-0.175676	-0.004386	0.000000	0.000000	0.017632
USAU	0.001165	0.134714	-0.065581	1.228916	-0.276596	-0.008081	-3.193619	-0.000200	-0.574459
WPM	0.004355	0.033102	-0.170535	0.098425	-0.090875	0.002732	-0.680274	-0.000042	0.929395

table.sort_values(by='Average Return Days')

	Returns	Risk	Sharpe Ratio	Max Returns	Min Returns	Median Returns	Total Return	Average Return Days	CAGR
GSV	0.002743	0.078153	-0.092857	0.378378	-0.270270	-0.011905	-7.042247	-0.000451	-0.023121
CDE	-0.001518	0.078391	-0.146934	0.346008	-0.186441	0.001678	-4.988124	-0.000316	-0.541128
GORO	0.000167	0.057420	-0.171243	0.146616	-0.180723	0.000000	-4.627251	-0.000292	-0.230688
CMCL	0.005892	0.050785	-0.080886	0.222910	-0.163722	0.003802	-3.854547	-0.000243	1.227861
KL	0.000665	0.047669	-0.195822	0.148540	-0.175737	0.001385	-3.339018	-0.000210	-0.078083
USAU	0.001165	0.134714	-0.065581	1.228916	-0.276596	-0.008081	-3.193619	-0.000200	-0.574459
RGLD	0.001991	0.047112	-0.170006	0.238794	-0.214262	0.001320	-3.033724	-0.000190	0.166741
SVM	0.000373	0.076470	-0.125894	0.371429	-0.237452	-0.005415	-2.499998	-0.000156	-0.337137
AXU	0.001783	0.065967	-0.124570	0.275510	-0.251969	-0.008130	-2.285712	-0.000143	-0.060501
SILV	0.003237	0.053523	-0.126360	0.186640	-0.169279	0.000000	-2.097903	-0.000131	0.369069
AUG	-0.000550	0.041567	-0.253818	0.104762	-0.137255	0.000000	-1.754384	-0.000109	-0.216319
MAG	0.002446	0.064114	-0.117825	0.286942	-0.212389	-0.000918	-1.143361	-0.000071	0.084323
AGI	0.004778	0.060617	-0.086149	0.290870	-0.192946	0.001764	-1.134927	-0.000070	0.674600
BTG	0.004370	0.052778	-0.106671	0.161074	-0.187861	0.004785	-0.959697	-0.000060	0.669365
MUX	-0.000310	0.055404	-0.186097	0.219472	-0.123905	0.000000	-0.949367	-0.000059	-0.270440
PAAS	0.002181	0.054527	-0.143393	0.234649	-0.210000	0.004337	-0.788131	-0.000049	0.126419
NEM	0.004958	0.034608	-0.145691	0.140182	-0.111161	0.004134	-0.746626	-0.000046	1.124296
WPM	0.004355	0.033102	-0.170535	0.098425	-0.090875	0.002732	-0.680274	-0.000042	0.929395
AEM	0.001426	0.039499	-0.217057	0.164597	-0.156319	0.000812	-0.495739	-0.000031	0.116850
DRD	0.009417	0.064093	-0.009097	0.234414	-0.201195	0.006622	-0.323632	-0.000020	2.574258
FNV	0.003750	0.032165	-0.194307	0.110634	-0.095818	0.003599	-0.233696	-0.000014	0.748085
EGO	0.002910	0.061169	-0.115909	0.320479	-0.193985	-0.001121	-0.112110	-0.000007	0.210574
TMQ	0.001344	0.050266	-0.172210	0.157895	-0.175676	-0.004386	0.000000	0.000000	0.017632
NG	0.005584	0.054173	-0.081512	0.276968	-0.117021	0.002328	0.000000	0.000000	1.054380
GOLD	0.004556	0.035489	-0.153390	0.151802	-0.103331	0.002731	0.076866	0.000005	0.971097
AUY	0.004270	0.050570	-0.113307	0.182432	-0.157143	0.004762	0.197234	0.000012	0.676337
AU	0.004299	0.057724	-0.098757	0.232181	-0.205929	0.002628	0.396984	0.000024	0.584840
KGC	0.005539	0.052840	-0.084430	0.190000	-0.153846	0.004132	0.434779	0.000027	1.048815
PLG	0.003272	0.076743	-0.087667	0.358974	-0.190141	0.000000	0.714285	0.000044	0.082430
IAG	0.001567	0.054417	-0.154973	0.211268	-0.190476	-0.003333	1.117317	0.000069	0.017434
PVG	-0.000308	0.051226	-0.201224	0.195804	-0.211076	-0.001940	1.210647	0.000074	-0.244365
GSS	-0.001672	0.043186	-0.270279	0.198157	-0.102459	0.000000	1.214574	0.000075	-0.359784
GFI	0.006066	0.067190	-0.058546	0.267813	-0.237589	0.004862	1.270647	0.000078	0.930777
AG	-0.001522	0.052698	-0.218639	0.205000	-0.141553	-0.005413	1.410252	0.000086	-0.393586
SAND	0.002849	0.054221	-0.131878	0.218415	-0.167969	0.001475	1.683939	0.000103	0.273505
FSM	0.001687	0.059565	-0.139564	0.219828	-0.225564	0.000000	1.863352	0.000114	-0.014063
OR	0.001986	0.049132	-0.163122	0.271357	-0.143855	0.002132	2.034257	0.000124	0.151788
EXK	-0.002053	0.056984	-0.211511	0.271930	-0.195804	-0.005952	4.411760	0.000267	-0.467793
SA	0.002890	0.059063	-0.120377	0.287157	-0.176201	0.003058	4.851550	0.000292	0.229353
HMY	0.004012	0.064018	-0.093535	0.168067	-0.249097	0.003135	5.763690	0.000346	0.397169